diff options
Diffstat (limited to 'delegate/src/test')
-rw-r--r-- | delegate/src/test/ArmnnDelegateTest.cpp | 32 | ||||
-rw-r--r-- | delegate/src/test/ElementwiseBinaryTest.cpp | 169 | ||||
-rw-r--r-- | delegate/src/test/ElementwiseBinaryTestHelper.hpp | 211 | ||||
-rw-r--r-- | delegate/src/test/ElementwiseUnaryTestHelper.hpp | 9 |
4 files changed, 403 insertions, 18 deletions
diff --git a/delegate/src/test/ArmnnDelegateTest.cpp b/delegate/src/test/ArmnnDelegateTest.cpp index fdf786ff99..7cec70b022 100644 --- a/delegate/src/test/ArmnnDelegateTest.cpp +++ b/delegate/src/test/ArmnnDelegateTest.cpp @@ -7,6 +7,7 @@ #include <doctest/doctest.h> #include <armnn_delegate.hpp> +#include "ElementwiseUnaryTestHelper.hpp" #include "tensorflow/lite/kernels/builtin_op_kernels.h" #include <tensorflow/lite/interpreter.h> @@ -19,30 +20,31 @@ TEST_SUITE("ArmnnDelegate") TEST_CASE ("ArmnnDelegate Registered") { - std::unique_ptr<tflite::impl::Interpreter> tfLiteInterpreter; - tfLiteInterpreter.reset(new tflite::impl::Interpreter); + using namespace tflite; + auto tfLiteInterpreter = std::make_unique<Interpreter>(); - // Create the network tfLiteInterpreter->AddTensors(3); - tfLiteInterpreter->SetInputs({0}); + tfLiteInterpreter->SetInputs({0, 1}); tfLiteInterpreter->SetOutputs({2}); - TfLiteQuantizationParams quantizationParams; - tfLiteInterpreter->SetTensorParametersReadWrite(0, kTfLiteFloat32, "", {3}, quantizationParams); - tfLiteInterpreter->SetTensorParametersReadWrite(1, kTfLiteFloat32, "", {3}, quantizationParams); - tfLiteInterpreter->SetTensorParametersReadWrite(2, kTfLiteFloat32, "", {3}, quantizationParams); - TfLiteRegistration* nodeRegistration = tflite::ops::builtin::Register_ABS(); - void* data = malloc(sizeof(int)); + tfLiteInterpreter->SetTensorParametersReadWrite(0, kTfLiteFloat32, "input1", {1,2,2,1}, TfLiteQuantization()); + tfLiteInterpreter->SetTensorParametersReadWrite(1, kTfLiteFloat32, "input2", {1,2,2,1}, TfLiteQuantization()); + tfLiteInterpreter->SetTensorParametersReadWrite(2, kTfLiteFloat32, "output", {1,2,2,1}, TfLiteQuantization()); - tfLiteInterpreter->AddNodeWithParameters({0}, {2}, nullptr, 0, data, nodeRegistration); + tflite::ops::builtin::BuiltinOpResolver opResolver; + const TfLiteRegistration* opRegister = opResolver.FindOp(BuiltinOperator_ADD, 1); + tfLiteInterpreter->AddNodeWithParameters({0, 1}, {2}, "", 0, nullptr, opRegister); // create the Armnn Delegate - auto delegateOptions = TfLiteArmnnDelegateOptionsDefault(); - auto delegate = TfLiteArmnnDelegateCreate(delegateOptions); - auto status = tfLiteInterpreter->ModifyGraphWithDelegate(std::move(delegate)); + std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef }; + armnnDelegate::DelegateOptions delegateOptions(backends); + std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)> + theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions), + armnnDelegate::TfLiteArmnnDelegateDelete); + + auto status = tfLiteInterpreter->ModifyGraphWithDelegate(std::move(theArmnnDelegate)); CHECK(status == kTfLiteOk); CHECK(tfLiteInterpreter != nullptr); - } } diff --git a/delegate/src/test/ElementwiseBinaryTest.cpp b/delegate/src/test/ElementwiseBinaryTest.cpp new file mode 100644 index 0000000000..bd4019a686 --- /dev/null +++ b/delegate/src/test/ElementwiseBinaryTest.cpp @@ -0,0 +1,169 @@ +// +// Copyright © 2020 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "ElementwiseBinaryTestHelper.hpp" + +#include <armnn_delegate.hpp> + +#include <flatbuffers/flatbuffers.h> +#include <tensorflow/lite/interpreter.h> +#include <tensorflow/lite/kernels/register.h> +#include <tensorflow/lite/model.h> +#include <tensorflow/lite/schema/schema_generated.h> +#include <tensorflow/lite/version.h> + +#include <doctest/doctest.h> + +namespace armnnDelegate +{ + +TEST_SUITE("ElementwiseBinaryTest") +{ + +TEST_CASE ("Add_Float32_GpuAcc_Test") +{ + // Create the ArmNN Delegate + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc, + armnn::Compute::CpuRef }; + // Set input data + std::vector<int32_t> input0Shape { 2, 2, 2, 3 }; + std::vector<int32_t> input1Shape { 2, 2, 2, 3 }; + std::vector<int32_t> outputShape { 2, 2, 2, 3 }; + + std::vector<float> input0Values = + { + 0.0f, 2.0f, 1.0f, + 0.2f, 1.0f, 2.0f, + + 1.0f, 2.0f, 1.0f, + 0.2f, 1.0f, 2.0f, + + 0.0f, 2.0f, 1.0f, + 4.2f, 1.0f, 2.0f, + + 0.0f, 0.0f, 1.0f, + 0.2f, 1.0f, 2.0f, + + }; + + std::vector<float> input1Values = + { + 1.0f, 2.0f, 1.0f, + 0.0f, 1.0f, 2.0f, + + 1.0f, 2.0f, -2.0f, + 0.2f, 1.0f, 2.0f, + + 0.0f, 2.0f, 1.0f, + 4.2f, 0.0f, -3.0f, + + 0.0f, 0.0f, 1.0f, + 0.7f, 1.0f, 5.0f, + }; + + std::vector<float> expectedOutputValues = + { + 1.0f, 4.0f, 2.0f, + 0.2f, 2.0f, 4.0f, + + 2.0f, 4.0f, -1.0f, + 0.4f, 2.0f, 4.0f, + + 0.0f, 4.0f, 2.0f, + 8.4f, 1.0f, -1.0f, + + 0.0f, 0.0f, 2.0f, + 0.9f, 2.0f, 7.0f, + }; + + + ElementwiseBinaryFP32Test(tflite::BuiltinOperator_ADD, + tflite::ActivationFunctionType_NONE, + backends, + input0Shape, + input1Shape, + outputShape, + input0Values, + input1Values, + expectedOutputValues); +} + +TEST_CASE ("Add_Broadcast_Float32_GpuAcc_Test") +{ + // Create the ArmNN Delegate + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc, + armnn::Compute::CpuRef }; + // Set input data + std::vector<int32_t> input0Shape { 1, 3, 2, 1 }; + std::vector<int32_t> input1Shape { 1, 1, 2, 3 }; + std::vector<int32_t> outputShape { 1, 3, 2, 3 }; + + std::vector<float> input0Values + { + 0.0f, + 1.0f, + + 2.0f, + 3.0f, + + 4.0f, + 5.0f, + }; + std::vector<float> input1Values + { + 0.5f, 1.5f, 2.5f, + 3.5f, 4.5f, 5.5f, + }; + // Set output data + std::vector<float> expectedOutputValues + { + 0.5f, 1.5f, 2.5f, + 4.5f, 5.5f, 6.5f, + + 2.5f, 3.5f, 4.5f, + 6.5f, 7.5f, 8.5f, + + 4.5f, 5.5f, 6.5f, + 8.5f, 9.5f, 10.5f, + }; + ElementwiseBinaryFP32Test(tflite::BuiltinOperator_ADD, + tflite::ActivationFunctionType_NONE, + backends, + input0Shape, + input1Shape, + outputShape, + input0Values, + input1Values, + expectedOutputValues); +} + +TEST_CASE ("Add_ActivationRELU_Float32_GpuAcc_Test") +{ + // Create the ArmNN Delegate + std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc, + armnn::Compute::CpuRef }; + // Set input data + std::vector<int32_t> input0Shape { 1, 2, 2, 1 }; + std::vector<int32_t> input1Shape { 1, 2, 2, 1 }; + std::vector<int32_t> outputShape { 1, 2, 2, 1 }; + + std::vector<float> input0Values { 4.0f, 0.8f, 0.7f, -0.8f }; + std::vector<float> input1Values { 0.7f, -1.2f, 0.8f, 0.5f }; + // Set output data + std::vector<float> expectedOutputValues { 4.7f, 0.0f, 1.5f, 0.0f }; + ElementwiseBinaryFP32Test(tflite::BuiltinOperator_ADD, + tflite::ActivationFunctionType_RELU, + backends, + input0Shape, + input1Shape, + outputShape, + input0Values, + input1Values, + expectedOutputValues); +} + +} + +} // namespace armnnDelegate
\ No newline at end of file diff --git a/delegate/src/test/ElementwiseBinaryTestHelper.hpp b/delegate/src/test/ElementwiseBinaryTestHelper.hpp new file mode 100644 index 0000000000..72f9f850c8 --- /dev/null +++ b/delegate/src/test/ElementwiseBinaryTestHelper.hpp @@ -0,0 +1,211 @@ +// +// Copyright © 2020 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include <armnn_delegate.hpp> + +#include <flatbuffers/flatbuffers.h> +#include <tensorflow/lite/interpreter.h> +#include <tensorflow/lite/kernels/register.h> +#include <tensorflow/lite/model.h> +#include <tensorflow/lite/schema/schema_generated.h> +#include <tensorflow/lite/version.h> + +#include <doctest/doctest.h> + +namespace +{ + +std::vector<char> CreateElementwiseBinaryTfLiteModel(tflite::BuiltinOperator binaryOperatorCode, + tflite::ActivationFunctionType activationType, + tflite::TensorType tensorType, + const std::vector <int32_t>& input0TensorShape, + const std::vector <int32_t>& input1TensorShape, + const std::vector <int32_t>& outputTensorShape) +{ + using namespace tflite; + flatbuffers::FlatBufferBuilder flatBufferBuilder; + + std::vector<flatbuffers::Offset<tflite::Buffer>> buffers; + buffers.push_back(CreateBuffer(flatBufferBuilder, flatBufferBuilder.CreateVector({}))); + + std::array<flatbuffers::Offset<Tensor>, 3> tensors; + tensors[0] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(input0TensorShape.data(), + input0TensorShape.size()), + tensorType, 0); + tensors[1] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(input1TensorShape.data(), + input1TensorShape.size()), + tensorType, 0); + tensors[2] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(), + outputTensorShape.size()), + tensorType); + + // create operator + tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_NONE; + flatbuffers::Offset<void> operatorBuiltinOptions = 0; + switch (binaryOperatorCode) + { + case BuiltinOperator_ADD: + { + operatorBuiltinOptionsType = BuiltinOptions_AddOptions; + operatorBuiltinOptions = CreateAddOptions(flatBufferBuilder, activationType).Union(); + break; + } + case BuiltinOperator_DIV: + { + operatorBuiltinOptionsType = BuiltinOptions_DivOptions; + operatorBuiltinOptions = CreateDivOptions(flatBufferBuilder, activationType).Union(); + break; + } + case BuiltinOperator_MUL: + { + operatorBuiltinOptionsType = BuiltinOptions_MulOptions; + operatorBuiltinOptions = CreateMulOptions(flatBufferBuilder, activationType).Union(); + break; + } + case BuiltinOperator_SUB: + { + operatorBuiltinOptionsType = BuiltinOptions_SubOptions; + operatorBuiltinOptions = CreateSubOptions(flatBufferBuilder, activationType).Union(); + break; + } + default: + break; + } + const std::vector<int32_t> operatorInputs{ {0, 1} }; + const std::vector<int32_t> operatorOutputs{{2}}; + flatbuffers::Offset <Operator> elementwiseBinaryOperator = + CreateOperator(flatBufferBuilder, + 0, + flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()), + flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()), + operatorBuiltinOptionsType, + operatorBuiltinOptions); + + const std::vector<int> subgraphInputs{ {0, 1} }; + const std::vector<int> subgraphOutputs{{2}}; + flatbuffers::Offset <SubGraph> subgraph = + CreateSubGraph(flatBufferBuilder, + flatBufferBuilder.CreateVector(tensors.data(), tensors.size()), + flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()), + flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()), + flatBufferBuilder.CreateVector(&elementwiseBinaryOperator, 1)); + + flatbuffers::Offset <flatbuffers::String> modelDescription = + flatBufferBuilder.CreateString("ArmnnDelegate: Elementwise Binary Operator Model"); + flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, binaryOperatorCode); + + flatbuffers::Offset <Model> flatbufferModel = + CreateModel(flatBufferBuilder, + TFLITE_SCHEMA_VERSION, + flatBufferBuilder.CreateVector(&operatorCode, 1), + flatBufferBuilder.CreateVector(&subgraph, 1), + modelDescription, + flatBufferBuilder.CreateVector(buffers.data(), buffers.size())); + + flatBufferBuilder.Finish(flatbufferModel); + + return std::vector<char>(flatBufferBuilder.GetBufferPointer(), + flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); +} + +void ElementwiseBinaryFP32Test(tflite::BuiltinOperator binaryOperatorCode, + tflite::ActivationFunctionType activationType, + std::vector<armnn::BackendId>& backends, + std::vector<int32_t>& input0Shape, + std::vector<int32_t>& input1Shape, + std::vector<int32_t>& outputShape, + std::vector<float>& input0Values, + std::vector<float>& input1Values, + std::vector<float>& expectedOutputValues) +{ + using namespace tflite; + std::vector<char> modelBuffer = CreateElementwiseBinaryTfLiteModel(binaryOperatorCode, + activationType, + ::tflite::TensorType_FLOAT32, + input0Shape, + input1Shape, + outputShape); + + const Model* tfLiteModel = GetModel(modelBuffer.data()); + // Create TfLite Interpreters + std::unique_ptr<Interpreter> armnnDelegateInterpreter; + CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver()) + (&armnnDelegateInterpreter) == kTfLiteOk); + CHECK(armnnDelegateInterpreter != nullptr); + CHECK(armnnDelegateInterpreter->AllocateTensors() == kTfLiteOk); + + std::unique_ptr<Interpreter> tfLiteInterpreter; + CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver()) + (&tfLiteInterpreter) == kTfLiteOk); + CHECK(tfLiteInterpreter != nullptr); + CHECK(tfLiteInterpreter->AllocateTensors() == kTfLiteOk); + + // Create the ArmNN Delegate + armnnDelegate::DelegateOptions delegateOptions(backends); + std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)> + theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions), + armnnDelegate::TfLiteArmnnDelegateDelete); + CHECK(theArmnnDelegate != nullptr); + // Modify armnnDelegateInterpreter to use armnnDelegate + CHECK(armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk); + + // Set input data + auto tfLiteDelegateInput0Id = tfLiteInterpreter->inputs()[0]; + auto tfLiteDelageInput0Data = tfLiteInterpreter->typed_tensor<float>(tfLiteDelegateInput0Id); + for (unsigned int i = 0; i < input0Values.size(); ++i) + { + tfLiteDelageInput0Data[i] = input0Values[i]; + } + + auto tfLiteDelegateInput1Id = tfLiteInterpreter->inputs()[1]; + auto tfLiteDelageInput1Data = tfLiteInterpreter->typed_tensor<float>(tfLiteDelegateInput1Id); + for (unsigned int i = 0; i < input1Values.size(); ++i) + { + tfLiteDelageInput1Data[i] = input1Values[i]; + } + + auto armnnDelegateInput0Id = armnnDelegateInterpreter->inputs()[0]; + auto armnnDelegateInput0Data = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateInput0Id); + for (unsigned int i = 0; i < input0Values.size(); ++i) + { + armnnDelegateInput0Data[i] = input0Values[i]; + } + + auto armnnDelegateInput1Id = armnnDelegateInterpreter->inputs()[1]; + auto armnnDelegateInput1Data = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateInput1Id); + for (unsigned int i = 0; i < input1Values.size(); ++i) + { + armnnDelegateInput1Data[i] = input1Values[i]; + } + + // Run EnqueWorkload + CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); + CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); + + // Compare output data + auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0]; + auto tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<float>(tfLiteDelegateOutputId); + auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0]; + auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<float>(armnnDelegateOutputId); + for (size_t i = 0; i < expectedOutputValues.size(); i++) + { + CHECK(expectedOutputValues[i] == armnnDelegateOutputData[i]); + CHECK(tfLiteDelageOutputData[i] == expectedOutputValues[i]); + CHECK(tfLiteDelageOutputData[i] == armnnDelegateOutputData[i]); + } + + armnnDelegateInterpreter.reset(nullptr); +} + +} // anonymous namespace + + + + diff --git a/delegate/src/test/ElementwiseUnaryTestHelper.hpp b/delegate/src/test/ElementwiseUnaryTestHelper.hpp index 4d45f4e964..b4a55cbe99 100644 --- a/delegate/src/test/ElementwiseUnaryTestHelper.hpp +++ b/delegate/src/test/ElementwiseUnaryTestHelper.hpp @@ -97,12 +97,15 @@ void ElementwiseUnaryFP32Test(tflite::BuiltinOperator unaryOperatorCode, (&tfLiteInterpreter) == kTfLiteOk); CHECK(tfLiteInterpreter != nullptr); CHECK(tfLiteInterpreter->AllocateTensors() == kTfLiteOk); + // Create the ArmNN Delegate armnnDelegate::DelegateOptions delegateOptions(backends); - auto armnnDelegate = TfLiteArmnnDelegateCreate(delegateOptions); - CHECK(armnnDelegate != nullptr); + std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)> + theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions), + armnnDelegate::TfLiteArmnnDelegateDelete); + CHECK(theArmnnDelegate != nullptr); // Modify armnnDelegateInterpreter to use armnnDelegate - CHECK(armnnDelegateInterpreter->ModifyGraphWithDelegate(armnnDelegate) == kTfLiteOk); + CHECK(armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk); // Set input data auto tfLiteDelegateInputId = tfLiteInterpreter->inputs()[0]; |